Towards Human-Level Understanding of Complex Process Engineering Schematics: A Pedagogical, Introspective Multi-Agent Framework for Open-Domain Question Answering

Understand

In the chemical and process industries, Process Flow Diagrams (PFDs) and Piping and Instrumentation Diagrams (P&IDs) are critical for design, construction, and maintenance.

• Recent advancements in Generative AI, such as Large Multimodal Models (LMMs) like GPT4 (Omni), have shown promise in understanding and interpreting process diagrams for Visual Question Answering (VQA).
• However, proprietary models pose data privacy risks, and their computational complexity prevents knowledge editing for domain-specific customization on consumer hardware.
• To overcome these challenges, we propose a secure, on-premises enterprise solution using a hierarchical, multi-agent Retrieval Augmented Generation (RAG) framework for open-domain question answering (ODQA) tasks, offering enhanced data privacy, explainability, and cost-effectiveness.